A time-efficient pattern reduction algorithm for k-means clustering

Ming Chao Chiang, Chun Wei Tsai, Chu Sing Yang

研究成果: Article同行評審

76 引文 斯高帕斯(Scopus)

摘要

This paper presents an efficient algorithm, called pattern reduction (PR), for reducing the computation time of k-means and k-means-based clustering algorithms. The proposed algorithm works by compressing and removing at each iteration patterns that are unlikely to change their membership thereafter. Not only is the proposed algorithm simple and easy to implement, but it can also be applied to many other iterative clustering algorithms such as kernel-based and population-based clustering algorithms. Our experiments - from 2 to 1000 dimensions and 150 to 10,000,000 patterns - indicate that with a small loss of quality, the proposed algorithm can significantly reduce the computation time of all state-of-the-art clustering algorithms evaluated in this paper, especially for large and high-dimensional data sets.

原文English
頁(從 - 到)716-731
頁數16
期刊Information sciences
181
發行號4
DOIs
出版狀態Published - 2011 二月 15

All Science Journal Classification (ASJC) codes

  • 軟體
  • 控制與系統工程
  • 理論電腦科學
  • 電腦科學應用
  • 資訊系統與管理
  • 人工智慧

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